The study was conducted as a Split-Plot-Design:
For a detailed description see the Metadata.
Participants of entire sample: N = 323
Participants per group:
tmp <- rawdata_np %>%
mutate(quelle = substr(Pseudonym, 1, 3),
kontext = substr(Pseudonym, 5, 6))
tmp_summ <- tmp %>%
group_by(quelle, kontext)%>%
summarize(n=n())| quelle | kontext | n |
|---|---|---|
| erf | mk | 53 |
| erf | ok | 59 |
| exp | mk | 53 |
| exp | ok | 57 |
| wis | mk | 50 |
| wis | ok | 51 |
tmp_fit <- aov(age ~ quelle + kontext + quelle:kontext, data=tmp)
summary(tmp_fit)## Df Sum Sq Mean Sq F value Pr(>F)
## quelle 2 44 21.8 1.39 0.25
## kontext 1 42 41.9 2.67 0.10
## quelle:kontext 2 58 29.1 1.85 0.16
## Residuals 316 4966 15.7
## 1 observation deleted due to missingness
rm(tmp_fit)
## Df Sum Sq Mean Sq F value Pr(>F)
## quelle 2 18 8.84 0.71 0.49
## kontext 1 18 17.96 1.45 0.23
## quelle:kontext 2 10 5.16 0.42 0.66
## Residuals 317 3929 12.39
## Df Sum Sq Mean Sq F value Pr(>F)
## quelle 2 34779 17390 1.61 0.20
## kontext 1 2578 2578 0.24 0.63
## quelle:kontext 2 7470 3735 0.35 0.71
## Residuals 303 3278649 10821
## 14 observations deleted due to missingness
## Df Sum Sq Mean Sq F value Pr(>F)
## quelle 2 0.5 0.272 0.69 0.50
## kontext 1 0.0 0.000 0.00 0.98
## quelle:kontext 2 0.3 0.139 0.35 0.70
## Residuals 312 123.6 0.396
## 5 observations deleted due to missingness
Measured once, either before or after presenting the intervention text (see Metadata).
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| te_01_np | 3.931 | 1.346 | 4 | 1 | 7 |
| te_02_np | 3.546 | 1.355 | 3 | 1 | 7 |
| te_03_np | 3.535 | 1.352 | 3 | 1 | 7 |
| te_04_np | 4.26 | 1.271 | 4 | 1 | 7 |
| te_05_np | 4.965 | 1.168 | 5 | 1 | 7 |
| te_06_np | 3.503 | 1.255 | 3 | 1 | 7 |
| te_07_np | 3.782 | 1.15 | 4 | 1 | 7 |
| te_08_np | 4.748 | 1.268 | 5 | 1 | 7 |
| te_09_np | 3.938 | 1.122 | 4 | 1 | 7 |
| te_10_np | 3.194 | 1.174 | 3 | 1 | 7 |
| vr_01_np | 3.962 | 1.354 | 4 | 1 | 7 |
| vr_02_np | 4.755 | 1.34 | 5 | 1 | 7 |
| vr_03_np | 4.587 | 1.343 | 5 | 1 | 7 |
| vr_04_np | 4.656 | 1.224 | 5 | 2 | 7 |
| vr_05_np | 5.095 | 1.251 | 5 | 2 | 7 |
| vr_06_np | 4.956 | 1.196 | 5 | 1 | 7 |
| vr_07_np | 5.362 | 1.145 | 5 | 2 | 7 |
# Model of factor analysis
modcaeb <- '
# latent variables
vr =~ vr_01_np + vr_02_np + vr_03_np + vr_04_np + vr_05_np + vr_06_np + vr_07_np
te =~ te_01_np + te_02_np + te_03_np + te_04_np + te_05_np +
te_06_np + te_07_np + te_08_np + te_09_np + te_10_np
# covariances, selected using modification indices
te_06_np ~~ te_10_np
vr_02_np ~~ vr_04_np
vr_05_np ~~ vr_07_np
vr_04_np ~~ vr_07_np
vr_01_np ~~ vr_07_np
vr_01_np ~~ vr_05_np
vr_02_np ~~ vr_07_np
te_03_np ~~ te_07_np
vr_06_np ~~ vr_07_np
vr_01_np ~~ vr_06_np
vr_02_np ~~ vr_05_np
'## Found more than one class "Model" in cache; using the first, from namespace 'lavaan'
| chisq | df | pvalue | cfi | tli | rmsea |
|---|---|---|---|---|---|
| 181.5 | 107 | 0 | 0.937 | 0.92 | 0.049 |
Item codes: tc_02_np, tc_05_np, tc_07_np, tc_08_np, tc_09_np, tc_10_np, tc_11_np, tc_01_np, tc_03_np, tc_04_np, tc_06_np, tc_12_np, ts_04_np, ts_06_np, ts_07_np, ts_10_np, ts_11_np, ts_12_np, ts_01_np, ts_02_np, ts_03_np, ts_05_np, ts_08_np, ts_09_np, tj_04_np, tj_06_np, tj_07_np, tj_10_np, tj_12_np, tj_13_np, tj_01_np, tj_02_np, tj_03_np, tj_05_np, tj_08_np, tj_09_np, tj_11_np, to_04_np, to_05_np, to_09_np, to_10_np, to_11_np, to_12_np, to_01_np, to_02_np, to_03_np, to_06_np, to_07_np, to_08_np
Descriptive item statistics:
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| tc_02_np | 4.559 | 1.156 | 5 | 1 | 6 |
| tc_05_np | 4.313 | 1.275 | 4 | 1 | 6 |
| tc_07_np | 4.246 | 1.379 | 5 | 1 | 6 |
| tc_08_np | 4.236 | 1.136 | 4 | 1 | 6 |
| tc_09_np | 4.415 | 1.496 | 5 | 1 | 6 |
| tc_10_np | 4.11 | 1.402 | 4 | 1 | 6 |
| tc_11_np | 4.259 | 1.264 | 4 | 1 | 6 |
| tc_01_np | 4.271 | 1.169 | 5 | 1 | 6 |
| tc_03_np | 5.048 | 1.007 | 5 | 1 | 6 |
| tc_04_np | 4.754 | 1.185 | 5 | 1 | 6 |
| tc_06_np | 4.105 | 1.616 | 4 | 1 | 6 |
| tc_12_np | 4.433 | 1.176 | 5 | 1 | 6 |
| ts_04_np | 3.975 | 1.14 | 4 | 1 | 6 |
| ts_06_np | 3.833 | 1.199 | 4 | 1 | 6 |
| ts_07_np | 4.978 | 0.946 | 5 | 1 | 6 |
| ts_10_np | 4.819 | 0.965 | 5 | 1 | 6 |
| ts_11_np | 4.598 | 1.057 | 5 | 1 | 6 |
| ts_12_np | 4.189 | 1.114 | 4 | 1 | 6 |
| ts_01_np | 3.575 | 1.409 | 4 | 1 | 6 |
| ts_02_np | 4.508 | 1.133 | 5 | 1 | 6 |
| ts_03_np | 4.229 | 1.286 | 5 | 1 | 6 |
| ts_05_np | 3.76 | 1.686 | 4 | 1 | 6 |
| ts_08_np | 3.654 | 1.167 | 4 | 1 | 6 |
| ts_09_np | 3.846 | 1.228 | 4 | 1 | 6 |
| tj_04_np | 3.324 | 1.343 | 3 | 1 | 6 |
| tj_06_np | 4.028 | 1.185 | 4 | 1 | 6 |
| tj_07_np | 3.94 | 1.362 | 4 | 1 | 6 |
| tj_10_np | 4.698 | 1.023 | 5 | 1 | 6 |
| tj_12_np | 4.834 | 1 | 5 | 1 | 6 |
| tj_13_np | 4.577 | 1.03 | 5 | 1 | 6 |
| tj_01_np | 2.918 | 1.31 | 3 | 1 | 6 |
| tj_02_np | 3.212 | 1.293 | 3 | 1 | 6 |
| tj_03_np | 3.76 | 1.397 | 4 | 1 | 6 |
| tj_05_np | 3.772 | 1.338 | 4 | 1 | 6 |
| tj_08_np | 2.579 | 1.186 | 2 | 1 | 6 |
| tj_09_np | 3.756 | 1.459 | 4 | 1 | 6 |
| tj_11_np | 3.935 | 1.195 | 4 | 1 | 6 |
| to_04_np | 4.994 | 1.103 | 5 | 1 | 6 |
| to_05_np | 4.969 | 1.096 | 5 | 1 | 6 |
| to_09_np | 4.293 | 1.252 | 5 | 1 | 6 |
| to_10_np | 4.7 | 1.047 | 5 | 1 | 6 |
| to_11_np | 4.195 | 1.178 | 4 | 1 | 6 |
| to_12_np | 4.826 | 0.913 | 5 | 1 | 6 |
| to_01_np | 4.119 | 1.398 | 4 | 1 | 6 |
| to_02_np | 3.433 | 1.232 | 3 | 1 | 6 |
| to_03_np | 4.089 | 1.44 | 4 | 1 | 6 |
| to_06_np | 4.939 | 1.115 | 5 | 1 | 6 |
| to_07_np | 4.538 | 1.088 | 5 | 1 | 6 |
| to_08_np | 4.325 | 1.198 | 4 | 1 | 6 |
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| si_01_np | 4.091 | 1.575 | 5 | 1 | 6 |
| si_02_np | 3.542 | 1.402 | 4 | 1 | 6 |
| si_05_np | 2.927 | 1.593 | 3 | 1 | 6 |
| si_07_np | 2.387 | 1.333 | 2 | 1 | 6 |
| si_03_np | 3.761 | 1.486 | 4 | 1 | 6 |
| si_04_np | 3.359 | 1.472 | 3 | 1 | 6 |
| si_06_np | 5.39 | 1.06 | 6 | 1 | 6 |
# Model of factor analysis
# latent variable
modin <- 'f1 =~ si_01_np + si_02_np + si_03_np + si_04_np + si_05_np + si_06_np + si_07_np
# covariances, selected using modification indices
si_01_np ~~ si_02_np'| chisq | df | pvalue | cfi | tli | rmsea |
|---|---|---|---|---|---|
| 32.25 | 13 | 0.002 | 0.972 | 0.954 | 0.07 |
Descriptive item statistics
| sex | n |
|---|---|
| male | 105 |
| female | 216 |
| other | 1 |
| NA | 1 |
| subject | n |
|---|---|
| faecher_1 | 1 |
| faecher_2 | 0 |
| faecher_3 | 34 |
| faecher_4 | 25 |
| faecher_5 | 97 |
| faecher_6 | 121 |
| faecher_7 | 19 |
| faecher_8 | 9 |
| faecher_9 | 20 |
| faecher_10 | 20 |
| faecher_11 | 73 |
| faecher_12 | 0 |
| faecher_13 | 4 |
| faecher_14 | 11 |
| faecher_15 | 15 |
| faecher_16 | 21 |
| faecher_17 | 38 |
| faecher_18 | 16 |
| faecher_19 | 35 |
| faecher_20 | 11 |
| faecher_21 | 21 |
| faecher_22 | 4 |
| faecher_23 | 29 |
| faecher_24 | 25 |
| faecher_25 | 7 |
| faecher_26 | 18 |
Descriptive item statistics (no school context group):
Descriptive item statistics (school context group):
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| cr_01_np | 3.505 | 1.467 | 4 | 1 | 6 |
| cr_02_np | 4.086 | 1.207 | 4 | 1 | 6 |
| ce_01_np | 3.273 | 1.355 | 3 | 1 | 6 |
| ce_02_np | 3.492 | 1.386 | 3 | 1 | 6 |
| cw_01_np | 4.066 | 1.518 | 4 | 1 | 6 |
| cw_02_np | 4.072 | 1.587 | 4 | 1 | 6 |
# Model of factor analysis
modtreso <- '
# latent variables, constraint on equal loadings
adv =~ NA*lambda1*cr_01_np
+ NA*lambda1*cr_02_np
rep =~ NA*lambda2*ce_01_np
+ NA*lambda2*ce_02_np
sci =~ NA*lambda3*cw_01_np
+ NA*lambda3*cw_02_np
# fix variance of latent variables
adv ~~ 1*adv
rep ~~ 1*rep
sci ~~ 1*sci
'
| chisq | df | pvalue | cfi | tli | rmsea |
|---|---|---|---|---|---|
| 52.17 | 12 | 0 | 0.911 | 0.888 | 0.106 |
# Import data
rawdata_li <- read.table("../Codebook/Textkomplexitaet.csv", sep=";", header=TRUE, na.strings = c("-99", "NA"))
pander(data.frame(select(rawdata_li, -Text)))| Vignette | LIX | Wortanzahl | Flesch |
|---|---|---|---|
| erf_mk_dd_we | 54,57 | 190 | 45 |
| erf_mk_dd_cm | 58,95 | 143 | 35 |
| erf_mk_ed_bp | 55,03 | 191 | 46 |
| erf_mk_ed_bm | 62,23 | 194 | 41 |
| erf_mk_gr_in | 55,89 | 149 | 55 |
| erf_mk_gr_gt | 53,79 | 145 | 50 |
| erf_ok_dd_we | 53,97 | 164 | 48 |
| erf_ok_dd_cm | 53,69 | 130 | 36 |
| erf_ok_ed_bp | 63,12 | 162 | 31 |
| erf_ok_ed_bm | 63,15 | 146 | 53 |
| erf_ok_gr_in | 55,35 | 131 | 53 |
| erf_ok_gr_gt | 57,42 | 151 | 35 |
| exp_mk_dd_we | 60,44 | 162 | 38 |
| exp_mk_dd_cm | 61,67 | 162 | 27 |
| exp_mk_ed_bp | 63,85 | 164 | 42 |
| exp_mk_ed_bm | 63,33 | 150 | 51 |
| exp_mk_gr_in | 63,83 | 146 | 42 |
| exp_mk_gr_gt | 61,33 | 150 | 27 |
| exp_ok_dd_we | 60,27 | 131 | 35 |
| exp_ok_dd_cm | 62,63 | 137 | 20 |
| exp_ok_ed_bp | 66,72 | 151 | 26 |
| exp_ok_ed_bm | 60,61 | 130 | 42 |
| exp_ok_gr_in | 65,23 | 130 | 38 |
| exp_ok_gr_gt | 63,37 | 166 | 29 |
| wis_mk_dd_we | 56,67 | 171 | 39 |
| wis_mk_dd_cm | 57,37 | 203 | 43 |
| wis_mk_ed_bp | 65,34 | 193 | 42 |
| wis_mk_ed_bm | 70,45 | 154 | 42 |
| wis_mk_gr_in | 58,18 | 165 | 36 |
| wis_mk_gr_gt | 58,67 | 197 | 28 |
| wis_ok_dd_we | 51,5 | 142 | 37 |
| wis_ok_dd_cm | 60,61 | 188 | 36 |
| wis_ok_ed_bp | 73,35 | 162 | 24 |
| wis_ok_ed_bm | 61,7 | 136 | 30 |
| wis_ok_gr_in | 58,25 | 153 | 32 |
| wis_ok_gr_gt | 57,38 | 178 | 18 |
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| si_11_np | 3.838 | 1.486 | 4 | 1 | 6 |
| si_12_np | 3.569 | 1.39 | 4 | 1 | 6 |
| si_15_np | 2.974 | 1.566 | 3 | 1 | 6 |
| si_17_np | 2.399 | 1.387 | 2 | 1 | 6 |
| si_13_np | 3.793 | 1.437 | 4 | 1 | 6 |
| si_14_np | 3.391 | 1.444 | 3 | 1 | 6 |
| si_16_np | 5.355 | 1.128 | 6 | 1 | 6 |
# Model of factor analysis
modin <- '
# latent variable
f1 =~ si_11_np + si_12_np + si_13_np + si_14_np + si_15_np + si_16_np + si_17_np'| chisq | df | pvalue | cfi | tli | rmsea |
|---|---|---|---|---|---|
| 55.18 | 14 | 0 | 0.946 | 0.919 | 0.101 |
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| sk_01_np | 2.763 | 0.627 | 3 | 1 | 4 |
| sk_02_np | 2.895 | 0.765 | 3 | 1 | 4 |
| sk_04_np | 2.866 | 0.68 | 3 | 1 | 4 |
| sk_03_np | 2.78 | 0.656 | 3 | 1 | 4 |
# Model of factor analysis
modFSK <- '
# latent variable
f1 =~ sk_01_np + sk_02_np + sk_03_np + sk_04_np'| chisq | df | pvalue | cfi | tli | rmsea |
|---|---|---|---|---|---|
| 55.18 | 14 | 0 | 0.946 | 0.919 | 0.101 |
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| ab_02_np | 3.074 | 1.543 | 3 | 1 | 6 |
| ab_03_np | 2.912 | 1.451 | 3 | 1 | 6 |
| ab_04_np | 2.853 | 1.545 | 3 | 1 | 6 |
| ab_05_np | 3.065 | 1.403 | 3 | 1 | 6 |
| ab_06_np | 2.397 | 1.422 | 2 | 1 | 6 |
| ab_07_np | 2.783 | 1.588 | 2 | 1 | 6 |
| ab_08_np | 2.828 | 1.441 | 3 | 1 | 6 |
| ab_09_np | 3.182 | 1.52 | 3 | 1 | 6 |
| ab_10_np | 2.662 | 1.319 | 2 | 1 | 6 |
| ab_11_np | 2.48 | 1.288 | 2 | 1 | 6 |
| ab_12_np | 2.983 | 1.601 | 3 | 1 | 6 |
| ab_01_np | 3.027 | 1.281 | 3 | 1 | 6 |
| ab_13_np | 1.931 | 1.173 | 2 | 1 | 6 |
| re_02_np | 3.078 | 1.36 | 3 | 1 | 6 |
| re_03_np | 3.186 | 1.408 | 3 | 1 | 6 |
| re_04_np | 4.427 | 1.371 | 5 | 1 | 6 |
| re_05_np | 4.456 | 1.334 | 5 | 1 | 6 |
| re_06_np | 4.003 | 1.477 | 4 | 1 | 6 |
| re_07_np | 3.569 | 1.615 | 4 | 1 | 6 |
| re_08_np | 4.275 | 1.486 | 4 | 1 | 6 |
| re_09_np | 3.526 | 1.473 | 4 | 1 | 6 |
| re_10_np | 3.512 | 1.38 | 4 | 1 | 6 |
| re_11_np | 3.91 | 1.276 | 4 | 1 | 6 |
| re_12_np | 3.893 | 1.398 | 4 | 1 | 6 |
| re_01_np | 3.248 | 1.214 | 3 | 1 | 6 |
| re_13_np | 3.97 | 1.464 | 4 | 1 | 6 |
| po_02_np | 4.374 | 1.347 | 5 | 1 | 6 |
| po_03_np | 4.145 | 1.258 | 4 | 1 | 6 |
| po_04_np | 4.366 | 1.131 | 4 | 1 | 6 |
| po_05_np | 4.342 | 1.08 | 4 | 1 | 6 |
| po_06_np | 4.786 | 1.148 | 5 | 1 | 6 |
| po_07_np | 3.379 | 1.677 | 3.5 | 1 | 6 |
| po_08_np | 3.86 | 1.197 | 4 | 1 | 6 |
| po_09_np | 4.246 | 1.288 | 4 | 1 | 6 |
| po_10_np | 3.838 | 1.16 | 4 | 1 | 6 |
| po_11_np | 3.917 | 1.221 | 4 | 1 | 6 |
| po_12_np | 4.351 | 1.101 | 4 | 1 | 6 |
| po_01_np | 4.23 | 1.135 | 4 | 1 | 6 |
| po_13_np | 4.254 | 1.069 | 4 | 1 | 6 |
Measured after every single of the six text vignettes
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| dd_we_im_01_np | 2.873 | 0.825 | 3 | 1 | 4 |
| dd_we_im_02_np | 2.349 | 0.94 | 2 | 1 | 4 |
| dd_we_im_03_np | 2.365 | 0.932 | 2 | 1 | 4 |
| dd_we_im_04_np | 2.514 | 0.984 | 3 | 1 | 4 |
| dd_cm_im_01_np | 3.08 | 0.837 | 3 | 1 | 4 |
| dd_cm_im_02_np | 2.59 | 0.957 | 3 | 1 | 4 |
| dd_cm_im_03_np | 2.564 | 0.95 | 3 | 1 | 4 |
| dd_cm_im_04_np | 2.606 | 0.945 | 3 | 1 | 4 |
| ed_bp_im_01_np | 3.006 | 0.828 | 3 | 1 | 4 |
| ed_bp_im_02_np | 2.506 | 0.914 | 3 | 1 | 4 |
| ed_bp_im_03_np | 2.561 | 0.959 | 3 | 1 | 4 |
| ed_bp_im_04_np | 2.565 | 0.952 | 3 | 1 | 4 |
| ed_bm_im_01_np | 3.298 | 0.731 | 3 | 1 | 4 |
| ed_bm_im_02_np | 2.755 | 0.846 | 3 | 1 | 4 |
| ed_bm_im_03_np | 2.823 | 0.902 | 3 | 1 | 4 |
| ed_bm_im_04_np | 2.837 | 0.939 | 3 | 1 | 4 |
| gr_in_im_01_np | 3.073 | 0.842 | 3 | 1 | 4 |
| gr_in_im_02_np | 2.569 | 0.904 | 3 | 1 | 4 |
| gr_in_im_03_np | 2.669 | 0.965 | 3 | 1 | 4 |
| gr_in_im_04_np | 2.696 | 0.963 | 3 | 1 | 4 |
| gr_gt_im_01_np | 2.654 | 0.849 | 3 | 1 | 4 |
| gr_gt_im_02_np | 2.155 | 0.85 | 2 | 1 | 4 |
| gr_gt_im_03_np | 2.168 | 0.885 | 2 | 1 | 4 |
| gr_gt_im_04_np | 2.405 | 0.92 | 2 | 1 | 4 |
| dd_we_im_05_np | 3.038 | 0.925 | 3 | 1 | 4 |
| dd_we_im_06_np | 3.304 | 0.899 | 4 | 1 | 4 |
| dd_we_im_07_np | 3.23 | 0.97 | 4 | 1 | 4 |
| dd_cm_im_05_np | 3.235 | 0.855 | 3 | 1 | 4 |
| dd_cm_im_06_np | 3.373 | 0.859 | 4 | 1 | 4 |
| dd_cm_im_07_np | 3.408 | 0.886 | 4 | 1 | 4 |
| ed_bp_im_05_np | 3.226 | 0.848 | 3 | 1 | 4 |
| ed_bp_im_06_np | 3.371 | 0.848 | 4 | 1 | 4 |
| ed_bp_im_07_np | 3.142 | 0.891 | 3.25 | 1 | 4 |
| ed_bm_im_05_np | 3.392 | 0.715 | 4 | 1 | 4 |
| ed_bm_im_06_np | 3.613 | 0.642 | 4 | 1 | 4 |
| ed_bm_im_07_np | 3.612 | 0.748 | 4 | 1 | 4 |
| gr_in_im_05_np | 3.288 | 0.856 | 3.5 | 1 | 4 |
| gr_in_im_06_np | 3.439 | 0.796 | 4 | 1 | 4 |
| gr_in_im_07_np | 3.398 | 0.868 | 4 | 1 | 4 |
| gr_gt_im_05_np | 2.912 | 0.909 | 3 | 1 | 4 |
| gr_gt_im_06_np | 3.119 | 0.966 | 3 | 1 | 4 |
| gr_gt_im_07_np | 3.126 | 0.989 | 3 | 1 | 4 |
library(MplusAutomation)
# Model of two-level confirmatory factor analysis
# Numeric clusteridentifier for MPlus
rawdata_long_np$IDnum <- as.numeric(as.factor(rawdata_long_np$Pseudonym))
# MPlus Model
MCFA_im <- mplusObject(
TITLE = "MCFA_imm",
ANALYSIS = "TYPE = TWOLEVEL;",
VARIABLE = "USEVARIABLES = im_01_np im_02_np im_03_np im_04_np
im_05_np im_06_np im_07_np;
CLUSTER = IDnum;",
MODEL = "%WITHIN%
IMW BY im_01_np im_02_np im_03_np im_04_np
im_05_np im_06_np im_07_np;
%BETWEEN%
IMB BY im_01_np im_02_np im_03_np im_04_np
im_05_np im_06_np im_07_np;
IM_04_NP WITH IM_02_NP;
IM_03_NP WITH IM_01_NP;
IM_03_NP WITH IM_02_NP;
IM_07_NP WITH IM_06_NP;
",
OUTPUT = "Standardized Modindices;",
rdata = rawdata_long_np)
MCFA_im_fit <- mplusModeler(MCFA_im, "mcfa_im.dat", run = 1)Reading model: mcfa_im.out
| ChiSqM_Value | ChiSqM_DF | ChiSqM_PValue | CFI | TLI | RMSEA_Estimate |
|---|---|---|---|---|---|
| 343.4 | 24 | 0 | 0.932 | 0.882 | 0.084 |
| SRMR.Within | SRMR.Between |
|---|---|
| 0.048 | 0.071 |
## Reading model: mcfa_im.out
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| dd_we_cl_01_np | 1.978 | 0.892 | 2 | 1 | 4 |
| dd_we_cl_02_np | 2.258 | 0.976 | 2 | 1 | 5 |
| dd_we_cl_03_np | 2.617 | 0.986 | 3 | 1 | 5 |
| dd_cm_cl_01_np | 1.795 | 0.843 | 2 | 1 | 5 |
| dd_cm_cl_02_np | 2.103 | 0.903 | 2 | 1 | 5 |
| dd_cm_cl_03_np | 2.381 | 1.01 | 2 | 1 | 5 |
| ed_bp_cl_01_np | 2.264 | 1.106 | 2 | 1 | 5 |
| ed_bp_cl_02_np | 2.439 | 1.028 | 2 | 1 | 5 |
| ed_bp_cl_03_np | 2.686 | 0.979 | 3 | 1 | 5 |
| ed_bm_cl_01_np | 1.524 | 0.705 | 1 | 1 | 4 |
| ed_bm_cl_02_np | 1.893 | 0.893 | 2 | 1 | 5 |
| ed_bm_cl_03_np | 2.266 | 0.964 | 2 | 1 | 5 |
| gr_in_cl_01_np | 1.852 | 0.841 | 2 | 1 | 5 |
| gr_in_cl_02_np | 2.218 | 1.038 | 2 | 1 | 5 |
| gr_in_cl_03_np | 2.391 | 0.978 | 2 | 1 | 5 |
| gr_gt_cl_01_np | 2.31 | 0.966 | 2 | 1 | 5 |
| gr_gt_cl_02_np | 2.431 | 0.994 | 2 | 1 | 5 |
| gr_gt_cl_03_np | 2.675 | 1.022 | 3 | 1 | 5 |
library(MplusAutomation)
# Model of two-level confirmatory factor analysis
# MPlus Model
MCFA_cl <- mplusObject(
TITLE = "MCFA_cl",
ANALYSIS = "TYPE = TWOLEVEL;",
VARIABLE = "USEVARIABLES = cl_01_np cl_02_np cl_03_np;
CLUSTER = IDnum;",
MODEL = "%WITHIN%
clW BY cl_01_np(1)
cl_02_np(2)
cl_03_np(3);
%BETWEEN%
clB BY cl_01_np(1)
cl_02_np(2)
cl_03_np(3);
",
OUTPUT = "Standardized Modindices;",
rdata = rawdata_long_np)
MCFA_cl_fit <- mplusModeler(MCFA_cl, "mcfa_cl.dat", run = 1)Reading model: mcfa_cl.out
| ChiSqM_Value | ChiSqM_DF | ChiSqM_PValue | CFI | TLI | RMSEA_Estimate |
|---|---|---|---|---|---|
| 12.62 | 2 | 0.002 | 0.976 | 0.929 | 0.053 |
| SRMR.Within | SRMR.Between |
|---|---|
| 0.012 | 0.079 |
## Reading model: mcfa_cl.out
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| dd_we_ie_01_np | 2.813 | 1.469 | 3 | 1 | 6 |
| dd_we_ie_02_np | 2.86 | 1.476 | 3 | 1 | 6 |
| dd_we_ie_03_np | 3.441 | 1.606 | 4 | 1 | 6 |
| dd_we_ie_04_np | 1.646 | 1.001 | 1 | 1 | 6 |
| dd_cm_ie_01_np | 3.126 | 1.518 | 3 | 1 | 6 |
| dd_cm_ie_02_np | 3.126 | 1.505 | 3 | 1 | 6 |
| dd_cm_ie_03_np | 3.702 | 1.504 | 4 | 1 | 6 |
| dd_cm_ie_04_np | 1.77 | 1.152 | 1 | 1 | 6 |
| ed_bp_ie_01_np | 3.067 | 1.496 | 3 | 1 | 6 |
| ed_bp_ie_02_np | 3.125 | 1.472 | 3 | 1 | 6 |
| ed_bp_ie_03_np | 3.761 | 1.455 | 4 | 1 | 6 |
| ed_bp_ie_04_np | 1.737 | 1.15 | 1 | 1 | 6 |
| ed_bm_ie_01_np | 3.397 | 1.501 | 4 | 1 | 6 |
| ed_bm_ie_02_np | 3.412 | 1.445 | 4 | 1 | 6 |
| ed_bm_ie_03_np | 4.029 | 1.396 | 4 | 1 | 6 |
| ed_bm_ie_04_np | 1.906 | 1.213 | 1 | 1 | 6 |
| gr_in_ie_01_np | 3.103 | 1.479 | 3 | 1 | 6 |
| gr_in_ie_02_np | 3.093 | 1.468 | 3 | 1 | 6 |
| gr_in_ie_03_np | 3.667 | 1.513 | 4 | 1 | 6 |
| gr_in_ie_04_np | 1.714 | 1.077 | 1 | 1 | 6 |
| gr_gt_ie_01_np | 2.476 | 1.369 | 2 | 1 | 6 |
| gr_gt_ie_02_np | 2.505 | 1.341 | 2 | 1 | 6 |
| gr_gt_ie_03_np | 3.208 | 1.482 | 3 | 1 | 6 |
| gr_gt_ie_04_np | 1.553 | 0.968 | 1 | 1 | 6 |
| dd_we_ie_05_np | 4.562 | 1.564 | 5 | 1 | 6 |
| dd_cm_ie_05_np | 4.923 | 1.407 | 5 | 1 | 6 |
| ed_bp_ie_05_np | 4.633 | 1.518 | 5 | 1 | 6 |
| ed_bm_ie_05_np | 5.091 | 1.265 | 6 | 1 | 6 |
| gr_in_ie_05_np | 4.736 | 1.466 | 5 | 1 | 6 |
| gr_gt_ie_05_np | 4.39 | 1.579 | 5 | 1 | 6 |
library(MplusAutomation)
# Model of two-level confirmatory factor analysis
# MPlus Model
MCFA_ie <- mplusObject(
TITLE = "MCFA_ie",
ANALYSIS = "TYPE = TWOLEVEL;",
VARIABLE = "USEVARIABLES = ie_01_np ie_02_np ie_03_np ie_04_np
ie_05_np;
CLUSTER = IDnum;",
MODEL = "%WITHIN%
ieW BY ie_01_np ie_02_np ie_03_np ie_04_np
ie_05_np;
%BETWEEN%
ieB BY ie_01_np ie_02_np ie_03_np ie_04_np
ie_05_np;
IE_05_NP WITH IE_03_NP;
IE_05_NP WITH IE_04_NP;
",
OUTPUT = "Standardized Modindices;",
rdata = rawdata_long_np)
MCFA_ie_fit <- mplusModeler(MCFA_ie, "mcfa_ie.dat", run = 1)Reading model: mcfa_ie.out
| ChiSqM_Value | ChiSqM_DF | ChiSqM_PValue | CFI | TLI | RMSEA_Estimate |
|---|---|---|---|---|---|
| 71.51 | 8 | 0 | 0.98 | 0.949 | 0.065 |
| SRMR.Within | SRMR.Between |
|---|---|
| 0.024 | 0.049 |
## Reading model: mcfa_ie.out
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| dd_we_tp_01_np | 2.971 | 0.93 | 3 | 1 | 4 |
| dd_we_tp_03_np | 3.052 | 0.834 | 3 | 1 | 4 |
| dd_we_tp_05_np | 2.913 | 0.83 | 3 | 1 | 4 |
| dd_cm_tp_01_np | 3.257 | 0.834 | 3 | 1 | 4 |
| dd_cm_tp_03_np | 3.309 | 0.754 | 3 | 1 | 4 |
| dd_cm_tp_05_np | 3.186 | 0.798 | 3 | 1 | 4 |
| ed_bp_tp_01_np | 2.787 | 0.921 | 3 | 1 | 4 |
| ed_bp_tp_03_np | 2.929 | 0.825 | 3 | 1 | 4 |
| ed_bp_tp_05_np | 2.656 | 0.868 | 3 | 1 | 4 |
| ed_bm_tp_01_np | 3.387 | 0.775 | 4 | 1 | 4 |
| ed_bm_tp_03_np | 3.308 | 0.769 | 3 | 1 | 4 |
| ed_bm_tp_05_np | 3.071 | 0.861 | 3 | 1 | 4 |
| gr_in_tp_01_np | 2.756 | 1.002 | 3 | 1 | 4 |
| gr_in_tp_03_np | 2.853 | 0.871 | 3 | 1 | 4 |
| gr_in_tp_05_np | 2.35 | 0.909 | 2 | 1 | 4 |
| gr_gt_tp_01_np | 2.475 | 0.946 | 3 | 1 | 4 |
| gr_gt_tp_03_np | 2.425 | 0.875 | 2 | 1 | 4 |
| gr_gt_tp_05_np | 2.303 | 0.883 | 2 | 1 | 4 |
| dd_we_tp_02_np | 2.825 | 0.967 | 3 | 1 | 4 |
| dd_we_tp_04_np | 2.19 | 0.91 | 2 | 1 | 4 |
| dd_we_tp_06_np | 2.841 | 0.818 | 3 | 1 | 4 |
| dd_cm_tp_02_np | 2.775 | 1.026 | 3 | 1 | 4 |
| dd_cm_tp_04_np | 2.206 | 0.983 | 2 | 1 | 4 |
| dd_cm_tp_06_np | 3.085 | 0.792 | 3 | 1 | 4 |
| ed_bp_tp_02_np | 2.761 | 0.925 | 3 | 1 | 4 |
| ed_bp_tp_04_np | 2.333 | 0.92 | 2 | 1 | 4 |
| ed_bp_tp_06_np | 2.576 | 0.836 | 3 | 1 | 4 |
| ed_bm_tp_02_np | 2.799 | 1.059 | 3 | 1 | 4 |
| ed_bm_tp_04_np | 2.817 | 0.961 | 3 | 1 | 4 |
| ed_bm_tp_06_np | 3.12 | 0.842 | 3 | 1 | 4 |
| gr_in_tp_02_np | 2.656 | 0.964 | 3 | 1 | 4 |
| gr_in_tp_04_np | 2.111 | 0.94 | 2 | 1 | 4 |
| gr_in_tp_06_np | 3.016 | 0.857 | 3 | 1 | 4 |
| gr_gt_tp_02_np | 2.611 | 0.939 | 3 | 1 | 4 |
| gr_gt_tp_04_np | 1.951 | 0.878 | 2 | 1 | 4 |
| gr_gt_tp_06_np | 2.733 | 0.94 | 3 | 1 | 4 |
library(MplusAutomation)
# Model of two-level confirmatory factor analysis
# MPlus Model
MCFA_tp<- mplusObject(
TITLE = "MCFA_tp",
ANALYSIS = "TYPE = TWOLEVEL;",
VARIABLE = "USEVARIABLES = tp_01_np tp_02_np tp_03_np tp_04_np
tp_05_np tp_06_np;
CLUSTER = IDnum;",
MODEL = "%WITHIN%
tpW BY tp_01_np tp_02_np tp_03_np tp_04_np
tp_05_np tp_06_np ;
%BETWEEN%
tpB BY tp_01_np tp_02_np tp_03_np tp_04_np
tp_05_np tp_06_np;",
OUTPUT = "Standardized Modindices;",
rdata = rawdata_long_np)
MCFA_tp_fit <- mplusModeler(MCFA_tp, "mcfa_tp.dat", run = 1)
Reading model: mcfa_tp.out
| ChiSqM_Value | ChiSqM_DF | ChiSqM_PValue | CFI | TLI | RMSEA_Estimate |
|---|---|---|---|---|---|
| 51.42 | 18 | 0 | 0.988 | 0.98 | 0.031 |
| SRMR.Within | SRMR.Between |
|---|---|
| 0.019 | 0.036 |
## Reading model: mcfa_tp.out
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| dd_we_tr_01_np | 1.92 | 0.749 | 2 | 1 | 4 |
| dd_we_tr_02_np | 2.119 | 0.896 | 2 | 1 | 4 |
| dd_we_tr_03_np | 2.062 | 0.919 | 2 | 1 | 4 |
| dd_we_tr_04_np | 2.35 | 0.886 | 2 | 1 | 4 |
| dd_cm_tr_01_np | 1.776 | 0.751 | 2 | 1 | 4 |
| dd_cm_tr_02_np | 1.792 | 0.789 | 2 | 1 | 4 |
| dd_cm_tr_03_np | 1.74 | 0.817 | 2 | 1 | 4 |
| dd_cm_tr_04_np | 1.948 | 0.855 | 2 | 1 | 4 |
| ed_bp_tr_01_np | 1.724 | 0.719 | 2 | 1 | 4 |
| ed_bp_tr_02_np | 1.866 | 0.805 | 2 | 1 | 4 |
| ed_bp_tr_03_np | 1.77 | 0.804 | 2 | 1 | 4 |
| ed_bp_tr_04_np | 2.033 | 0.827 | 2 | 1 | 4 |
| ed_bm_tr_01_np | 1.88 | 0.755 | 2 | 1 | 4 |
| ed_bm_tr_02_np | 1.787 | 0.825 | 2 | 1 | 4 |
| ed_bm_tr_03_np | 1.576 | 0.751 | 1 | 1 | 4 |
| ed_bm_tr_04_np | 1.925 | 0.865 | 2 | 1 | 4 |
| gr_in_tr_01_np | 1.931 | 0.795 | 2 | 1 | 4 |
| gr_in_tr_02_np | 2.117 | 0.865 | 2 | 1 | 4 |
| gr_in_tr_03_np | 2.023 | 0.95 | 2 | 1 | 4 |
| gr_in_tr_04_np | 2.272 | 0.904 | 2 | 1 | 4 |
| gr_gt_tr_01_np | 1.997 | 0.768 | 2 | 1 | 4 |
| gr_gt_tr_02_np | 2.266 | 0.889 | 2 | 1 | 4 |
| gr_gt_tr_03_np | 1.993 | 0.845 | 2 | 1 | 4 |
| gr_gt_tr_04_np | 2.298 | 0.846 | 2 | 1 | 4 |
library(MplusAutomation)
# Model of two-level confirmatory factor analysis
# MPlus Model
MCFA_tr <- mplusObject(
TITLE = "MCFA_tr",
ANALYSIS = "TYPE = TWOLEVEL;",
VARIABLE = "USEVARIABLES = tr_01_np tr_02_np tr_03_np tr_04_np;
CLUSTER = IDnum;",
MODEL = "%WITHIN%
trW BY tr_01_np tr_02_np tr_03_np tr_04_np;
%BETWEEN%
trB BY tr_01_np tr_02_np tr_03_np tr_04_np",
OUTPUT = "Standardized Modindices;",
rdata = rawdata_long_np)
MCFA_tr_fit <- mplusModeler(MCFA_tr, "mcfa_tr.dat", run = 1)
Reading model: mcfa_tr.out
| ChiSqM_Value | ChiSqM_DF | ChiSqM_PValue | CFI | TLI | RMSEA_Estimate |
|---|---|---|---|---|---|
| 38.71 | 4 | 0 | 0.958 | 0.875 | 0.068 |
| SRMR.Within | SRMR.Between |
|---|---|
| 0.031 | 0.069 |
## Reading model: mcfa_tr.out
*Descriptive score statistics and reliability estimates: all-day school + Arithmetic mean = 2.138 + Standarddeviation = 0.623
+ Range = [1, 4] + McDonalds \(\omega\) = 0.735, 95%-CI = [0.688, 0.781 ] + Smoothed Densityplot
library(MplusAutomation)
# Model of two-level confirmatory factor analysis
# MPlus Model
MCFA_ee <- mplusObject(
TITLE = "MCFA_ee",
ANALYSIS = "TYPE = TWOLEVEL;",
VARIABLE = "USEVARIABLES = su_01_np su_02_np su_03_np
cu_01_np cu_02_np cu_03_np
ex_01_np ex_02_np ex_03_np
bo_01_np bo_02_np bo_03_np;
CLUSTER = IDnum;",
MODEL = "%WITHIN%
suW BY su_01_np(1)
su_02_np(2)
su_03_np(3);
cuW BY cu_01_np(4)
cu_02_np(5)
cu_03_np(6);
exW BY ex_01_np(7)
ex_02_np(8)
ex_03_np(9);
boW BY bo_01_np(10)
bo_02_np(11)
bo_03_np(12);
%BETWEEN%
suB BY su_01_np(1)
su_02_np(2)
su_03_np(3);
cuB BY cu_01_np(4)
cu_02_np(5)
cu_03_np(6);
exB BY ex_01_np(7)
ex_02_np(8)
ex_03_np(9);
boB BY bo_01_np(10)
bo_02_np(11)
bo_03_np(12);",
OUTPUT = "Standardized Modindices;",
rdata = rawdata_long_np)
MCFA_ee_fit <- mplusModeler(MCFA_ee, "mcfa_ee.dat", run = 1)
Reading model: mcfa_ee.out
| ChiSqM_Value | ChiSqM_DF | ChiSqM_PValue | CFI | TLI | RMSEA_Estimate |
|---|---|---|---|---|---|
| 882 | 104 | 0 | 0.916 | 0.893 | 0.063 |
| SRMR.Within | SRMR.Between |
|---|---|
| 0.051 | 0.066 |
## Reading model: mcfa_ee.out
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| dd_we_su_01_np | 2.417 | 1.039 | 2 | 1 | 5 |
| dd_we_su_02_np | 2.547 | 1.027 | 3 | 1 | 5 |
| dd_we_su_03_np | 2.273 | 1.042 | 2 | 1 | 5 |
| dd_cm_su_01_np | 2 | 0.903 | 2 | 1 | 5 |
| dd_cm_su_02_np | 2.209 | 0.928 | 2 | 1 | 4 |
| dd_cm_su_03_np | 1.997 | 0.905 | 2 | 1 | 5 |
| ed_bp_su_01_np | 2.091 | 0.949 | 2 | 1 | 4 |
| ed_bp_su_02_np | 2.243 | 0.962 | 2 | 1 | 5 |
| ed_bp_su_03_np | 2.033 | 0.939 | 2 | 1 | 5 |
| ed_bm_su_01_np | 2.195 | 1.034 | 2 | 1 | 5 |
| ed_bm_su_02_np | 2.382 | 1.078 | 2 | 1 | 5 |
| ed_bm_su_03_np | 2.21 | 1.024 | 2 | 1 | 5 |
| gr_in_su_01_np | 2.165 | 0.944 | 2 | 1 | 4 |
| gr_in_su_02_np | 2.286 | 0.929 | 2 | 1 | 4 |
| gr_in_su_03_np | 2.231 | 1.017 | 2 | 1 | 5 |
| gr_gt_su_01_np | 2.087 | 0.934 | 2 | 1 | 5 |
| gr_gt_su_02_np | 2.153 | 0.942 | 2 | 1 | 5 |
| gr_gt_su_03_np | 2.066 | 0.888 | 2 | 1 | 5 |
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| dd_we_cu_01_np | 3.064 | 1.172 | 3 | 1 | 5 |
| dd_we_cu_02_np | 3.235 | 1.091 | 3 | 1 | 5 |
| dd_we_cu_03_np | 3.154 | 1.145 | 3 | 1 | 5 |
| dd_cm_cu_01_np | 3.152 | 1.171 | 3 | 1 | 5 |
| dd_cm_cu_02_np | 3.343 | 1.122 | 4 | 1 | 5 |
| dd_cm_cu_03_np | 3.199 | 1.132 | 3 | 1 | 5 |
| ed_bp_cu_01_np | 3.158 | 1.135 | 3 | 1 | 5 |
| ed_bp_cu_02_np | 3.349 | 1.051 | 3 | 1 | 5 |
| ed_bp_cu_03_np | 3.253 | 1.04 | 3 | 1 | 5 |
| ed_bm_cu_01_np | 3.409 | 1.131 | 4 | 1 | 5 |
| ed_bm_cu_02_np | 3.615 | 1.015 | 4 | 1 | 5 |
| ed_bm_cu_03_np | 3.436 | 1.096 | 4 | 1 | 5 |
| gr_in_cu_01_np | 3.204 | 1.084 | 3 | 1 | 5 |
| gr_in_cu_02_np | 3.327 | 1.105 | 3 | 1 | 5 |
| gr_in_cu_03_np | 3.205 | 1.095 | 3 | 1 | 5 |
| gr_gt_cu_01_np | 2.802 | 1.108 | 3 | 1 | 5 |
| gr_gt_cu_02_np | 2.89 | 1.11 | 3 | 1 | 5 |
| gr_gt_cu_03_np | 2.781 | 1.114 | 3 | 1 | 5 |
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| dd_we_ex_01_np | 2.479 | 1.047 | 3 | 1 | 5 |
| dd_we_ex_02_np | 2.246 | 0.989 | 2 | 1 | 5 |
| dd_we_ex_03_np | 2.305 | 1.013 | 2 | 1 | 5 |
| dd_cm_ex_01_np | 2.698 | 1.098 | 3 | 1 | 5 |
| dd_cm_ex_02_np | 2.328 | 1.044 | 2 | 1 | 5 |
| dd_cm_ex_03_np | 2.384 | 1.052 | 3 | 1 | 5 |
| ed_bp_ex_01_np | 2.571 | 1.026 | 3 | 1 | 5 |
| ed_bp_ex_02_np | 2.319 | 0.988 | 2 | 1 | 5 |
| ed_bp_ex_03_np | 2.351 | 0.983 | 2 | 1 | 5 |
| ed_bm_ex_01_np | 2.688 | 1.077 | 3 | 1 | 5 |
| ed_bm_ex_02_np | 2.297 | 0.998 | 2 | 1 | 5 |
| ed_bm_ex_03_np | 2.353 | 1.038 | 2 | 1 | 5 |
| gr_in_ex_01_np | 2.482 | 1.014 | 3 | 1 | 5 |
| gr_in_ex_02_np | 2.28 | 0.98 | 2 | 1 | 5 |
| gr_in_ex_03_np | 2.346 | 1.02 | 2 | 1 | 5 |
| gr_gt_ex_01_np | 2.184 | 0.978 | 2 | 1 | 5 |
| gr_gt_ex_02_np | 2.079 | 0.942 | 2 | 1 | 5 |
| gr_gt_ex_03_np | 2.119 | 0.934 | 2 | 1 | 5 |
| Mean | Stdev | Median | Minimum | Maximum | |
|---|---|---|---|---|---|
| dd_we_bo_01_np | 2.436 | 1.174 | 2 | 1 | 5 |
| dd_we_bo_02_np | 2.577 | 1.251 | 3 | 1 | 5 |
| dd_we_bo_03_np | 2.668 | 1.266 | 3 | 1 | 5 |
| dd_cm_bo_01_np | 2.341 | 1.234 | 2 | 1 | 5 |
| dd_cm_bo_02_np | 2.291 | 1.256 | 2 | 1 | 5 |
| dd_cm_bo_03_np | 2.32 | 1.221 | 2 | 1 | 5 |
| ed_bp_bo_01_np | 2.482 | 1.229 | 2 | 1 | 5 |
| ed_bp_bo_02_np | 2.533 | 1.226 | 2 | 1 | 5 |
| ed_bp_bo_03_np | 2.603 | 1.271 | 3 | 1 | 5 |
| ed_bm_bo_01_np | 2.162 | 1.066 | 2 | 1 | 5 |
| ed_bm_bo_02_np | 2.143 | 1.115 | 2 | 1 | 5 |
| ed_bm_bo_03_np | 2.257 | 1.113 | 2 | 1 | 5 |
| gr_in_bo_01_np | 2.379 | 1.188 | 2 | 1 | 5 |
| gr_in_bo_02_np | 2.479 | 1.197 | 2 | 1 | 5 |
| gr_in_bo_03_np | 2.528 | 1.17 | 2 | 1 | 5 |
| gr_gt_bo_01_np | 2.751 | 1.264 | 3 | 1 | 5 |
| gr_gt_bo_02_np | 2.713 | 1.259 | 3 | 1 | 5 |
| gr_gt_bo_03_np | 2.693 | 1.298 | 3 | 1 | 5 |